Slit Style HOG Feature for Document Image Word Spotting

Kengo Terasawa, Yuzuru Tanaka
{"title":"Slit Style HOG Feature for Document Image Word Spotting","authors":"Kengo Terasawa, Yuzuru Tanaka","doi":"10.1109/ICDAR.2009.118","DOIUrl":null,"url":null,"abstract":"This paper presents a word spotting method based on line-segmentation, sliding window, continuous dynamic programming, and slit style HOG feature. Our method is applicable regardless of what language is written in the manuscript because it does not require any language-dependent preprocess. The slit style HOG feature is a gradient-distribution-based feature with overlapping normalization and redundant expression, and the use of this feature improved the performance of the word spotting. We compared our method with some previously developed word spotting methods, and confirmed that our method outperforms them in both English and Japanese manuscripts.","PeriodicalId":433762,"journal":{"name":"2009 10th International Conference on Document Analysis and Recognition","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"101","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 10th International Conference on Document Analysis and Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.2009.118","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 101

Abstract

This paper presents a word spotting method based on line-segmentation, sliding window, continuous dynamic programming, and slit style HOG feature. Our method is applicable regardless of what language is written in the manuscript because it does not require any language-dependent preprocess. The slit style HOG feature is a gradient-distribution-based feature with overlapping normalization and redundant expression, and the use of this feature improved the performance of the word spotting. We compared our method with some previously developed word spotting methods, and confirmed that our method outperforms them in both English and Japanese manuscripts.
狭缝风格HOG特征的文件图像单词识别
本文提出了一种基于直线分割、滑动窗口、连续动态规划和裂隙式HOG特征的词识别方法。我们的方法是适用的,不管什么语言写在手稿中,因为它不需要任何语言相关的预处理。割缝式HOG特征是一种基于梯度分布的特征,具有重叠归一化和冗余表达,该特征的使用提高了单词识别的性能。我们将我们的方法与之前开发的一些单词识别方法进行了比较,并证实我们的方法在英语和日语手稿中都优于它们。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信